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Kasner M, Fritsche AH, Leong MC, Cameron K, Lee CB, Lin TL, Lee JH, Brogan F, Kovak MR, Honeycutt H, Shaw K, George TJ. North American Cancer Center Clinical Research Capacity and Benchmarking in the Postpandemic Era. JCO Oncol Pract 2024:OP2400164. [PMID: 38950320 DOI: 10.1200/op.24.00164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Revised: 05/21/2024] [Accepted: 06/06/2024] [Indexed: 07/03/2024] Open
Abstract
PURPOSE Cancer center clinical trial offices (CCTOs) support trial development, activation, conduct, regulatory adherence, data integrity, and compliance. In 2018, the Association of American Cancer Institutes (AACI) Clinical Research Innovation (CRI) Steering Committee conducted and published survey results to benchmark North American CCTOs, including trial volume, accrual, full time equivalents (FTEs), and budget. The survey was readministered in 2023 to assess contemporary CCTO performance and capacity with results presented here. METHODS The 28 question 2023 survey was sent to directors of AACI's clinical member cancer centers. Survey participation was voluntary, no compensation was provided, and data requested covered operations during 2022. Definitions were consistent with National Cancer Institute (NCI) CCTO reporting requirements and AACI staff anonymously compiled results for descriptive statistical reporting. RESULTS The survey response rate was 61% (60/99). The median annual CCTO budget was $11.5 million (M) US dollars (USD) versus $8.2M USD in 2018. These budgets support a median of 150 FTEs versus 104 previously, and a median total of 384 versus 280 interventional treatment trials and a median of 479 versus 531 interventional treatment accruals. Sources of support for CCTO annual budgets were primarily from industry revenue (45.3%) or institutional support (31.7%). Nearly 60% of centers reported activating NCI-sponsored studies within 90 days but only 9% reported meeting a 90-day activation timeline for industry sponsored studies. CONCLUSION Contemporary benchmarks for CCTO operations through this survey demonstrate larger staff sizes, larger budgets, more trials supported, but fewer patients enrolled to interventional treatment trials in comparison with 2018. These data shine a critical light on the increasing complexity of cancer clinical trials, the importance of external funding sources, and necessary operational efficiency upgrades to provide cutting-edge cancer research and care.
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Affiliation(s)
- Margaret Kasner
- Sidney Kimmel Cancer Center at Jefferson Health, Philadelphia, PA
| | | | - Man Chong Leong
- Department of Biostatistics, University of Florida, Gainesville, FL
| | - Kendra Cameron
- Association of American Cancer Institutes, Pittsburgh, PA
| | - Carrie B Lee
- UNC Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, NC
| | - Tara L Lin
- The University of Kansas Cancer Center, Kansas City, KS
| | - Ji-Hyun Lee
- Department of Biostatistics, University of Florida, Gainesville, FL
- University of Florida Health Cancer Center, Gainesville, FL
| | - Frances Brogan
- Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, NY, New York
| | - Matthew R Kovak
- UAMS Winthrop P. Rockefeller Cancer Institute, Little Rock, AR
| | | | - Kate Shaw
- Association of American Cancer Institutes, Pittsburgh, PA
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Dehar N, Meem M, Aggarwal I, Hopman W, Gaudreau PO, Robinson A, Fung AS. Brief Report: Real-World Eligibility for Clinical Trials in Patients With Extensive-Stage SCLC at a Tertiary Care Center. JTO Clin Res Rep 2024; 5:100696. [PMID: 39091596 PMCID: PMC11293570 DOI: 10.1016/j.jtocrr.2024.100696] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 04/22/2024] [Accepted: 06/02/2024] [Indexed: 08/04/2024] Open
Abstract
Introduction The CASPIAN and IMpower133 trials revealed a significant survival benefit of chemotherapy plus immunotherapy in patients with extensive-stage SCLC. The current study characterizes the proportion of real-world patients who would have met eligibility for these trials and highlights factors influencing eligibility in the real-world setting. Methods A retrospective analysis of patient data was conducted for stage IV patients with SCLC treated at the Cancer Centre of Southeastern Ontario, Canada. Trial eligibility was based on criteria used in the IMpower133 and CASPIAN trials. Data were summarized using descriptive statistics. Overall survival was assessed using the Kaplan-Meier method. Results Of the 116 patients included, only 12.1% met the overall eligibility criteria for the IMpower133 trial, and 14.7% for the CASPIAN trial. The most common reasons for ineligibility included: Eastern Cooperative Oncology Group (ECOG) 2 or greater (77.5%), inadequate organ function (48%), and the presence of brain metastases at diagnosis (37.3%). Sixty-one patients (59.8%) met two or more major ineligibility criteria. If trial eligibility was expanded to include ECOG 2 patients, an additional 10.3% would have met eligibility. The median overall survival for all-comers was 6.5 months. Conclusions Only a small minority of real-world patients with extensive-stage SCLC would have met eligibility for the IMpower133 and CASPIAN trials, with ECOG greater than or equal to 2, inadequate organ function, and brain metastases comprising the most common reasons for trial ineligibility. Future clinical trials should expand the inclusion criteria to better represent real-world patient populations.
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Affiliation(s)
- Navdeep Dehar
- Department of Oncology, Queen’s School of Medicine, Queen’s University, Kingston, Ontario, Canada
- Cancer Centre of Southeastern Ontario, Kingston Health Sciences Centre, Kingston, Ontario, Canada
| | - Mahbuba Meem
- Department of Oncology, Queen’s School of Medicine, Queen’s University, Kingston, Ontario, Canada
- Cancer Centre of Southeastern Ontario, Kingston Health Sciences Centre, Kingston, Ontario, Canada
| | - Ishita Aggarwal
- Department of Oncology, Queen’s School of Medicine, Queen’s University, Kingston, Ontario, Canada
- Cancer Centre of Southeastern Ontario, Kingston Health Sciences Centre, Kingston, Ontario, Canada
| | - Wilma Hopman
- Department of Oncology, Queen’s School of Medicine, Queen’s University, Kingston, Ontario, Canada
| | - Pierre-Olivier Gaudreau
- Department of Oncology, Queen’s School of Medicine, Queen’s University, Kingston, Ontario, Canada
- Cancer Centre of Southeastern Ontario, Kingston Health Sciences Centre, Kingston, Ontario, Canada
| | - Andrew Robinson
- Department of Oncology, Queen’s School of Medicine, Queen’s University, Kingston, Ontario, Canada
- Cancer Centre of Southeastern Ontario, Kingston Health Sciences Centre, Kingston, Ontario, Canada
| | - Andrea S. Fung
- Department of Oncology, Queen’s School of Medicine, Queen’s University, Kingston, Ontario, Canada
- Cancer Centre of Southeastern Ontario, Kingston Health Sciences Centre, Kingston, Ontario, Canada
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Mittal A, Moore S, Navani V, Jiang DM, Stewart DJ, Liu G, Wheatley-Price P. What Is Ailing Oncology Clinical Trials? Can We Fix Them? Curr Oncol 2024; 31:3738-3751. [PMID: 39057147 PMCID: PMC11276279 DOI: 10.3390/curroncol31070275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2024] [Revised: 06/21/2024] [Accepted: 06/24/2024] [Indexed: 07/28/2024] Open
Abstract
Evidence from phase three clinical trials helps shape clinical practice. However, a very small minority of patients with cancer participate in clinical trials and many trials are not completed on time due to slow accrual. Issues with restrictive eligibility criteria can severely limit the patients who can access trials, without any convincing evidence that these restrictions impact patient safety. Similarly, regulatory, organizational, and institutional hurdles can delay trial activation, ultimately making some studies irrelevant. Additional issues during trial conduct (e.g., mandatory in-person visits, central confirmation of standard biomarkers, and inflexible drug dosage modification) contribute to making trials non-patient-centric. These real-life observations from experienced clinical trialists can seem nonsensical to investigators and patients alike, who are trying to bring effective drugs to patients with cancer. In this review, we delve into these issues in detail, and discuss potential solutions to make clinical trials more accessible to patients.
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Affiliation(s)
- Abhenil Mittal
- North East Cancer Center, Health Sciences North, Northern Ontario School of Medicine (NOSM U), Sudbury, ON P3E5J1, Canada;
| | - Sara Moore
- Department of Medicine, Division of Medical Oncology, The Ottawa Hospital Cancer Centre, University of Ottawa, Ottawa, ON K1H8L6, Canada
| | - Vishal Navani
- Tom Baker Cancer Center, Alberta Health Services, Calgary, AB T2N4N2, Canada
- Cumming School of Medicine, University of Calgary, Calgary, AB T2N4N2, Canada
| | - Di Maria Jiang
- Princess Margaret Cancer Centre, University Health Network, University of Toronto, Toronto, ON M5G2M9, Canada (G.L.)
| | - David J. Stewart
- Department of Medicine, Division of Medical Oncology, The Ottawa Hospital Cancer Centre, University of Ottawa, Ottawa, ON K1H8L6, Canada
| | - Geoffrey Liu
- Princess Margaret Cancer Centre, University Health Network, University of Toronto, Toronto, ON M5G2M9, Canada (G.L.)
| | - Paul Wheatley-Price
- Department of Medicine, Division of Medical Oncology, The Ottawa Hospital Cancer Centre, University of Ottawa, Ottawa, ON K1H8L6, Canada
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Huang H, Jia S, Wang X, Miao H, Fang H, He H, Wu D, Tang Y, Li N. Quantitative evaluation of the impact of relaxing eligibility criteria on the risk-benefit profile of drugs for lung cancer based on real-world data. Thorac Cancer 2024; 15:1187-1194. [PMID: 38576119 DOI: 10.1111/1759-7714.15269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2024] [Accepted: 02/12/2024] [Indexed: 04/06/2024] Open
Abstract
INTRODUCTION Restrictive eligibility criteria in cancer drug trials result in low enrollment rates and limited population diversity. Relaxed eligibility criteria (REC) based on solid evidence is becoming necessary for stakeholders worldwide. However, the absence of high-quality, favorable evidence remains a major challenge. This study presents a protocol to quantitatively evaluate the impact of relaxing eligibility criteria in common non-small cell lung cancer (NSCLC) protocols in China, on the risk-benefit profile. This involves a detailed explanation of the rationale, framework, and design of REC. METHODS To evaluate our REC in NSCLC drug trials, we will first construct a structured, cross-dimensional real-world NSCLC database using deep learning methods. We will then establish randomized virtual cohorts and perform benefit-risk assessment using Monte Carlo simulation and propensity matching. Shapley value will be utilized to quantitatively measure the effect of the change of each eligibility criterion on patient volume, clinical efficacy and safety. DISCUSSION This study is one of the few that focuses on the problem of overly stringent eligibility criteria cancer drug clinical trials, providing quantitative evaluation of the effect of relaxing each NSCLC eligibility criterion. This study will not only provide scientific evidence for the rational design of population inclusion in lung cancer clinical trials, but also establish a data governance system, as well as a REC evaluation framework that can be generalized to other cancer studies.
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Affiliation(s)
- Huiyao Huang
- Clinical Trials Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Shuopeng Jia
- Clinical Trials Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xin Wang
- Clinical Trials Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Huilei Miao
- Clinical Trials Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Hong Fang
- Clinical Trials Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Hanqing He
- Clinical Trials Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Dawei Wu
- Clinical Trials Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yu Tang
- Clinical Trials Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ning Li
- Clinical Trials Center, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Atallah E. Eligibility criteria: too big, too small or just right? Haematologica 2024; 109:1021. [PMID: 37822257 PMCID: PMC10985446 DOI: 10.3324/haematol.2023.283972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 10/02/2023] [Indexed: 10/13/2023] Open
Abstract
Not available.
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Affiliation(s)
- Ehab Atallah
- Division of Hematology and Oncology Medical College of Wisconsin 9200 W. Wisconsin Ave, Milwaukee WI 53226.
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Kowalczyk E, Borysowski J, Ordak M, Kniotek M, Radziwoń-Zaleska M, Siwek M. Placebo-controlled randomized clinical trials of antidepressants for major depressive disorder: Analysis of ClinicalTrials.gov, 2008-2022. Psychiatry Res 2024; 333:115730. [PMID: 38245978 DOI: 10.1016/j.psychres.2024.115730] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 01/08/2024] [Accepted: 01/10/2024] [Indexed: 01/23/2024]
Abstract
The purpose of this study was to analyze the key aspects of the design of contemporary placebo-controlled randomized clinical trials (RCTs) of antidepressants enrolling patients with major depressive disorder (MDD) aged 18 years or older, especially the outcome measures and the eligibility criteria. The study included 122 RCTs registered with ClinicalTrials.gov and started from 2008 through 2022. Most RCTs assessed only clinical remission, with proportion of trials with outcome measures related to functional remission being rather low (n = 34; 28 %). Clinical remission was mostly evaluated in acute phase of depression, and only 7 (6 %) trials assessed the prevention of relapse. Proportion of trials utilizing self-report questionnaires that provide important information complementary to clinician-rated scales was moderate (n = 66; 54 %). Another problem in included RCTs was common use of stringent eligibility criteria. For instance, minimal symtpom severity required for the patient's inclusion was listed in 104 RCTs (85 %), and 41 RCTs (34 %) excluded patients based on comorbid anxiety disorders. Most RCTs (n = 103; 84 %) excluded older patients, and only 6 (5 %) trials were dedicated exclusively to them. To ensure optimal development of clinical pharmacotherapy of MDD, the investigators should consider modification of some of the key aspects of the design of RCTs of antidepressants.
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Affiliation(s)
- Ewa Kowalczyk
- Clinical Research Development Centre, Medical Research Agency, Moniuszki 1A 00-014, Warsaw, Poland
| | - Jan Borysowski
- Department of Clinical Immunology, Medical University of Warsaw, Nowogrodzka 59 02-006, Warsaw, Poland.
| | - Michał Ordak
- Department of Pharmacotherapy and Pharmaceutical Care, Faculty of Pharmacy, Medical University of Warsaw, Banacha 1 02-097, Warsaw, Poland
| | - Monika Kniotek
- Department of Clinical Immunology, Medical University of Warsaw, Nowogrodzka 59 02-006, Warsaw, Poland
| | - Maria Radziwoń-Zaleska
- Department of Psychiatry, Medical University of Warsaw, Nowowiejska 27 00-665, Warsaw, Poland
| | - Marcin Siwek
- Department of Affective Disorders, Chair of Psychiatry, Jagiellonian University Medical College, M. Kopernika 21 A 31-501, Kraków, Poland
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Ebrahimi H, Castro DV, Feng MI, Prajapati SR, Lee KO, Chan EH, Paul T, Sehgal I, Patel J, Li X, Zengin ZB, Meza L, Mercier BD, Hsu J, Govindarajan A, Chawla N, Dizman N, Bergerot CD, Rock A, Liu S, Tripathi A, Dorff T, Pal SK, Chehrazi-Raffle A. Examining Exclusion Criteria in Advanced Prostate Cancer Clinical Trials: An Assessment of recommendations From the American Society Of Clinical Oncology and Friends of Cancer Research. Clin Genitourin Cancer 2023; 21:e467-e473. [PMID: 37301665 DOI: 10.1016/j.clgc.2023.05.013] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 05/18/2023] [Accepted: 05/21/2023] [Indexed: 06/12/2023]
Abstract
PURPOSE Eligibility criteria illustrate the characteristics of the study population and promote the safety of participants. However, overreliance on restrictive eligibility criteria may limit the generalizability of outcomes. As a result, the American Society of Clinical Oncology (ASCO) and Friends of Cancer Research (Friends) issued statements to curtail these challenges. In this study, we aimed to assess restrictiveness in eligibility criteria across advanced prostate cancer clinical trials. MATERIALS AND METHODS We identified all phase I, II, and III advanced prostate cancer clinical trials between June 30, 2012, and June 30, 2022, through Clinicaltrials.gov. We evaluated whether a clinical trial excluded, conditionally included, or did not report 4 common criteria: brain metastases, prior or concurrent malignancies, HIV infection, and hepatitis B virus (HBV)/hepatitis C virus (HCV) infection. Performance status (PS) criteria were recorded based on the Eastern Cooperative Oncology Group (ECOG) scale. RESULTS Out of 699 clinical trials within our search strategy, 265 (37.9%) trials possessed all the required data and were included in our analysis. The most common excluded condition of our interest was brain metastases (60.8%), followed by HIV positivity (46.4%), HBV/HCV positivity (46.0%), and concurrent malignancies (15.5%). Additionally, 50.9% of clinical trials only included patients with ECOG PS 0 to 1. HIV and HBV/HCV infection were exclusion criteria of 22 (80.8%) and 19 (73.1%) immunotherapy trials, respectively. CONCLUSION Patients with brain metastases, prior or concurrent malignancies, HIV infection, HBV/HCV infection, or low-functioning PS were overly restricted from participating in advanced prostate clinical trials. Advocating for broader criteria may ameliorate generalizability.
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Affiliation(s)
- Hedyeh Ebrahimi
- Department of Medical Oncology & Experimental Therapeutics, City of Hope Comprehensive Cancer Center, Duarte, CA
| | - Daniela V Castro
- Department of Medical Oncology & Experimental Therapeutics, City of Hope Comprehensive Cancer Center, Duarte, CA
| | - Matthew I Feng
- Department of Medical Oncology & Experimental Therapeutics, City of Hope Comprehensive Cancer Center, Duarte, CA
| | - Sweta R Prajapati
- Department of Medical Oncology & Experimental Therapeutics, City of Hope Comprehensive Cancer Center, Duarte, CA
| | - Kyle O Lee
- Department of Medical Oncology & Experimental Therapeutics, City of Hope Comprehensive Cancer Center, Duarte, CA
| | - Elyse H Chan
- Department of Medical Oncology & Experimental Therapeutics, City of Hope Comprehensive Cancer Center, Duarte, CA
| | - Trishita Paul
- Department of Medical Oncology & Experimental Therapeutics, City of Hope Comprehensive Cancer Center, Duarte, CA
| | - Ishaan Sehgal
- Department of Medical Oncology & Experimental Therapeutics, City of Hope Comprehensive Cancer Center, Duarte, CA
| | - Jalen Patel
- Department of Medical Oncology & Experimental Therapeutics, City of Hope Comprehensive Cancer Center, Duarte, CA
| | - Xiaochan Li
- Department of Medical Oncology & Experimental Therapeutics, City of Hope Comprehensive Cancer Center, Duarte, CA
| | - Zeynep B Zengin
- Department of Medical Oncology & Experimental Therapeutics, City of Hope Comprehensive Cancer Center, Duarte, CA
| | - Luis Meza
- Department of Medical Oncology & Experimental Therapeutics, City of Hope Comprehensive Cancer Center, Duarte, CA
| | - Benjamin D Mercier
- Department of Medical Oncology & Experimental Therapeutics, City of Hope Comprehensive Cancer Center, Duarte, CA
| | - JoAnn Hsu
- Department of Medical Oncology & Experimental Therapeutics, City of Hope Comprehensive Cancer Center, Duarte, CA
| | - Ameish Govindarajan
- Department of Medical Oncology & Experimental Therapeutics, City of Hope Comprehensive Cancer Center, Duarte, CA
| | - Neal Chawla
- Department of Medical Oncology & Experimental Therapeutics, City of Hope Comprehensive Cancer Center, Duarte, CA
| | - Nazli Dizman
- Department of Medical Oncology & Experimental Therapeutics, City of Hope Comprehensive Cancer Center, Duarte, CA; Department of Internal Medicine, Yale University School of Medicine, Yale New Haven Hospital, New Haven, CT
| | - Cristiane D Bergerot
- Centro de Câncer de Brasília (CETTRO), Instituto Unity de Ensino e Pesquisa, Brasília, Brazil
| | - Adam Rock
- Department of Medical Oncology & Experimental Therapeutics, City of Hope Comprehensive Cancer Center, Duarte, CA
| | - Sandy Liu
- Department of Medical Oncology, City of Hope Orange County Medical Center, Irvine, CA
| | - Abhishek Tripathi
- Department of Medical Oncology & Experimental Therapeutics, City of Hope Comprehensive Cancer Center, Duarte, CA
| | - Tanya Dorff
- Department of Medical Oncology & Experimental Therapeutics, City of Hope Comprehensive Cancer Center, Duarte, CA
| | - Sumanta K Pal
- Department of Medical Oncology & Experimental Therapeutics, City of Hope Comprehensive Cancer Center, Duarte, CA
| | - Alexander Chehrazi-Raffle
- Department of Medical Oncology & Experimental Therapeutics, City of Hope Comprehensive Cancer Center, Duarte, CA.
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Uehara Y, Koyama T, Katsuya Y, Sato J, Sudo K, Kondo S, Yoshida T, Shoji H, Shimoi T, Yonemori K, Yamamoto N. Travel Time and Distance and Participation in Precision Oncology Trials at the National Cancer Center Hospital. JAMA Netw Open 2023; 6:e2333188. [PMID: 37713200 PMCID: PMC10504617 DOI: 10.1001/jamanetworkopen.2023.33188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 08/01/2023] [Indexed: 09/16/2023] Open
Abstract
Importance Genotype-matched trials, which are becoming increasingly important in the precision oncology era, require referrals from institutions providing comprehensive genomic profiling (CGP) testing to those conducting these trials, and the travel burden for trial participation is significant. However, it remains unknown whether travel time or distance are associated with genotype-matched trial participation. Objective To assess whether travel time or distance are associated with disparities in genotype-matched trial participation following CGP testing. Design, Setting, and Participants This retrospective cohort study from June 2020 to June 2022 included patients with advanced or metastatic solid tumors referred to the National Cancer Center Hospital for participation in genotype-matched trials following CGP testing and discussion by molecular tumor boards. Data were analyzed from June to October 2022. Exposures Travel time and distance. Main Outcomes and Measures The primary and secondary outcomes were enrollment in genotype-matched trials and all-cancer clinical trials, respectively. Results Of 1127 patients (mean [range] age, 62 [16-85] years; 584 women [52%]; all residents of Japan), 127 (11%) and 241 (21%) were enrolled in genotype-matched trials and all-cancer clinical trials, respectively. The overall median (IQR) travel distance and time were 38 (21-107) km and 55 (35-110) minutes, respectively. On multivariable regression with 23 covariates, travel distance (≥100 km vs <100 km) was not associated with the likelihood of genotype-matched trial participation (26 of 310 patients [8%] vs 101 of 807 patients [12%]; odds ratio [OR], 0.64; 95% CI, 0.40-1.02), whereas in patients with travel time of 120 minutes or more, the likelihood of genotype-matched trial participation was significantly lower than those with travel time less than 120 minutes (19 of 276 patients [7%] vs 108 of 851 patients [13%]; OR, 0.51; 95% CI, 0.29-0.84). The likelihood of genotype-matched trial participation decreased as travel time increased from less than 40 (38 of 283 patients [13%]) to 40 to 120 (70 of 568 patients [12%]) and 120 or more (19 of 276 patients [7%]) minutes (OR, 0.74; 95% CI, 0.48-1.17; OR, 0.41; 95% CI, 0.22-0.74, respectively). Neither travel time nor distance were associated with the likelihood of all-cancer clinical trial participation. Conclusions and Relevance In this cohort study of patients undergoing CGP testing, an increased travel time was associated with a decreased likelihood of genotype-matched trial participation. This warrants further research on interventions, such as decentralization of clinical trials to mitigate travel burden.
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Affiliation(s)
- Yuji Uehara
- Department of Experimental Therapeutics, National Cancer Center Hospital, Tokyo, Japan
- Department of Thoracic Oncology and Respiratory Medicine, Tokyo Metropolitan Cancer and Infectious Diseases Center, Komagome Hospital, Tokyo, Japan
- Department of Precision Cancer Medicine, Center for Innovative Cancer Treatment, Tokyo Medical and Dental University, Tokyo, Japan
| | - Takafumi Koyama
- Department of Experimental Therapeutics, National Cancer Center Hospital, Tokyo, Japan
| | - Yuki Katsuya
- Department of Experimental Therapeutics, National Cancer Center Hospital, Tokyo, Japan
| | - Jun Sato
- Department of Experimental Therapeutics, National Cancer Center Hospital, Tokyo, Japan
| | - Kazuki Sudo
- Department of Experimental Therapeutics, National Cancer Center Hospital, Tokyo, Japan
- Department of Medical Oncology, National Cancer Center Hospital, Tokyo, Japan
| | - Shunsuke Kondo
- Department of Experimental Therapeutics, National Cancer Center Hospital, Tokyo, Japan
- Department of Hepatobiliary and Pancreatic Oncology, National Cancer Center Hospital, Tokyo, Japan
| | - Tatsuya Yoshida
- Department of Experimental Therapeutics, National Cancer Center Hospital, Tokyo, Japan
- Department of Thoracic Oncology, National Cancer Center Hospital, Tokyo, Japan
| | - Hirokazu Shoji
- Department of Experimental Therapeutics, National Cancer Center Hospital, Tokyo, Japan
- Department of Gastrointestinal Medical Oncology, National Cancer Center Hospital, Tokyo, Japan
| | - Tatsunori Shimoi
- Department of Medical Oncology, National Cancer Center Hospital, Tokyo, Japan
| | - Kan Yonemori
- Department of Experimental Therapeutics, National Cancer Center Hospital, Tokyo, Japan
- Department of Medical Oncology, National Cancer Center Hospital, Tokyo, Japan
| | - Noboru Yamamoto
- Department of Experimental Therapeutics, National Cancer Center Hospital, Tokyo, Japan
- Department of Thoracic Oncology, National Cancer Center Hospital, Tokyo, Japan
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Kempf E, Vaterkowski M, Leprovost D, Griffon N, Ouagne D, Breant S, Serre P, Mouchet A, Rance B, Chatellier G, Bellamine A, Frank M, Guerin J, Tannier X, Livartowski A, Hilka M, Daniel C. How to Improve Cancer Patients ENrollment in Clinical Trials From rEal-Life Databases Using the Observational Medical Outcomes Partnership Oncology Extension: Results of the PENELOPE Initiative in Urologic Cancers. JCO Clin Cancer Inform 2023; 7:e2200179. [PMID: 37167578 DOI: 10.1200/cci.22.00179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/13/2023] Open
Abstract
PURPOSE To compare the computability of Observational Medical Outcomes Partnership (OMOP)-based queries related to prescreening of patients using two versions of the OMOP common data model (CDM; v5.3 and v5.4) and to assess the performance of the Greater Paris University Hospital (APHP) prescreening tool. MATERIALS AND METHODS We identified the prescreening information items being relevant for prescreening of patients with cancer. We randomly selected 15 academic and industry-sponsored urology phase I-IV clinical trials (CTs) launched at APHP between 2016 and 2021. The computability of the related prescreening criteria (PC) was defined by their translation rate in OMOP-compliant queries and by their execution rate on the APHP clinical data warehouse (CDW) containing data of 205,977 patients with cancer. The overall performance of the prescreening tool was assessed by the rate of true- and false-positive cases of three randomly selected CTs. RESULTS We defined a list of 15 minimal information items being relevant for patients' prescreening. We identified 83 PC of the 534 eligibility criteria from the 15 CTs. We translated 33 and 62 PC in queries on the basis of OMOP CDM v5.3 and v5.4, respectively (translation rates of 40% and 75%, respectively). Of the 33 PC translated in the v5.3 of the OMOP CDM, 19 could be executed on the APHP CDW (execution rate of 58%). Of 83 PC, the computability rate on the APHP CDW reached 23%. On the basis of three CTs, we identified 17, 32, and 63 patients as being potentially eligible for inclusion in those CTs, resulting in positive predictive values of 53%, 41%, and 21%, respectively. CONCLUSION We showed that PC could be formalized according to the OMOP CDM and that the oncology extension increased their translation rate through better representation of cancer natural history.
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Affiliation(s)
- Emmanuelle Kempf
- Sorbonne Université, Inserm, Université Sorbonne Paris Nord, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances pour la e-Santé, LIMICS, Paris, France
- Department of Medical Oncology, Assistance Publique Hôpitaux de Paris, Henri Mondor Teaching Hospital, Créteil, France
| | - Morgan Vaterkowski
- Innovation and Data, Paris, IT Department, Assistance Publique Hôpitaux de Paris, Paris, France
- EPITA School of Engineering and Computer Science, Paris, France
| | - Damien Leprovost
- Sorbonne Université, Inserm, Université Sorbonne Paris Nord, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances pour la e-Santé, LIMICS, Paris, France
- Innovation and Data, Paris, IT Department, Assistance Publique Hôpitaux de Paris, Paris, France
| | - Nicolas Griffon
- Sorbonne Université, Inserm, Université Sorbonne Paris Nord, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances pour la e-Santé, LIMICS, Paris, France
- Innovation and Data, Paris, IT Department, Assistance Publique Hôpitaux de Paris, Paris, France
| | - David Ouagne
- Innovation and Data, Paris, IT Department, Assistance Publique Hôpitaux de Paris, Paris, France
| | - Stéphane Breant
- Innovation and Data, Paris, IT Department, Assistance Publique Hôpitaux de Paris, Paris, France
| | - Patricia Serre
- Innovation and Data, Paris, IT Department, Assistance Publique Hôpitaux de Paris, Paris, France
| | - Alexandre Mouchet
- Innovation and Data, Paris, IT Department, Assistance Publique Hôpitaux de Paris, Paris, France
| | - Bastien Rance
- Department of Medical Informatics, Assistance Publique Hôpitaux de Paris, Centre-Université de Paris (APHP-CUP), Université de Paris, Paris, France
| | - Gilles Chatellier
- Department of Medical Informatics, Assistance Publique Hôpitaux de Paris, Centre-Université de Paris (APHP-CUP), Université de Paris, Paris, France
| | - Ali Bellamine
- Innovation and Data, Paris, IT Department, Assistance Publique Hôpitaux de Paris, Paris, France
| | - Marie Frank
- Department of Medical Information, Paris Saclay Teaching Hospital, Assistance Publique Hôpitaux de Paris, Paris, France
| | | | - Xavier Tannier
- Sorbonne Université, Inserm, Université Sorbonne Paris Nord, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances pour la e-Santé, LIMICS, Paris, France
| | | | - Martin Hilka
- Innovation and Data, Paris, IT Department, Assistance Publique Hôpitaux de Paris, Paris, France
| | - Christel Daniel
- Sorbonne Université, Inserm, Université Sorbonne Paris Nord, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances pour la e-Santé, LIMICS, Paris, France
- Innovation and Data, Paris, IT Department, Assistance Publique Hôpitaux de Paris, Paris, France
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